Scoping the Problem

Maternal Mortality Rates: New York, New York City, and U.S.

I’m interested in examining Maternal Mortality Rates in counties across New York State, with special emphasis on the five boroughs of New York City. Here I’ll create a maternal mortality rate, exmaine trends, and visualize the data with maps.

Loading libraries

library(tidyverse)

## Loading tidyverse: ggplot2
## Loading tidyverse: tibble
## Loading tidyverse: tidyr
## Loading tidyverse: readr
## Loading tidyverse: purrr
## Loading tidyverse: dplyr

## Conflicts with tidy packages ----------------------------------------------

## filter(): dplyr, stats
## lag():    dplyr, stats

library(tidycensus)
library(dplyr)
library(janitor)
library(ggplot2)
library(tmap)
library(tmaptools)
library(sf)

## Linking to GEOS 3.4.2, GDAL 2.1.2, proj.4 4.9.1

library(leaflet)
library(plyr)

## -------------------------------------------------------------------------

## You have loaded plyr after dplyr - this is likely to cause problems.
## If you need functions from both plyr and dplyr, please load plyr first, then dplyr:
## library(plyr); library(dplyr)

## -------------------------------------------------------------------------

## 
## Attaching package: 'plyr'

## The following objects are masked from 'package:dplyr':
## 
##     arrange, count, desc, failwith, id, mutate, rename, summarise,
##     summarize

## The following object is masked from 'package:purrr':
## 
##     compact

Reading in Maternal Mortality Data from https://www.health.ny.gov/statistics/chac/birth/b33.htm

maternal_deaths <- read_csv("/Users/cecilialow-weiner/Desktop/Data Incubator Project /2013_maternal_mortality_rate.csv")

## Parsed with column specification:
## cols(
##   boro_name = col_character(),
##   Live_Births = col_integer(),
##   Maternal_deaths = col_integer()
## )

Calculate Maternal Mortality

Maternal Mortality is death within 42 dats of pregnancy termination due to complications of pregnancy, childbirth, and the peurperium. The Rate of Maternal Mortality is calculated by the number of maternal deaths in a specified geographic area divded by total resident live births for the same geographic area within a specified time, multiplied by 100,000. (Source: CDC, 2007)

maternal_mortality_rate <- maternal_deaths %>%
  group_by(boro_name) %>%
  mutate(rate=(Maternal_deaths/Live_Births)*100000)

Scatterplot of Maternal Mortality Rate by Borough

ggplot(data = maternal_mortality_rate) + 
  geom_point(mapping = aes(x = Live_Births, y = Maternal_deaths, color=boro_name))

Bar chart of Maternal Mortality Rate by Borough

ggplot(data=maternal_mortality_rate, aes(x=boro_name, y=rate, fill=boro_name)) +
  geom_bar(stat="identity") +
scale_fill_brewer(palette = "Set2", name = element_blank()) +
  scale_y_continuous(labels = scales::percent) +
  labs(
    x = "Borough Name",
    y = "Maternal Mortality Rate",
    title = "Maternal Mortality Rate by Borough")

Mapping Maternal Mortality in New York City

Simple chloropeth map of maternal mortality rate in NYC

borough <- "/Users/cecilialow-weiner/Downloads/Borough Boundaries/geo_export_838ba8d5-de6d-49a7-a7a6-681c253a5cf5.shp"
nyc_boroughs <- read_shape(file=borough, as.sf = TRUE)
qtm(nyc_boroughs)

merged_borough <- merge(nyc_boroughs,maternal_mortality_rate,by="boro_name")


tm_shape(merged_borough) +
  tm_fill(
    col = "rate",
    n = 5,
    style = "jenks"
  )

Interactive map of maternal mortality rate by borough

ttm()

## tmap mode set to interactive viewing

tm_shape(merged_borough) +
  tm_fill(
    col = "rate",
    palette = "GnBu",
    contrast = c(0.2, 0.8),
    n = 5,
    style = "jenks",
    title = "Maternal Mortality Rate",
    legend.format = list(
      fun = function(x) {
        paste0(formatC(x, digits = 1 , format = "f"), "%")
      }
    ),
    popup.vars = c(
      "Maternal Mortality Rate" = "rate"
    ),
    id = "NAME",
    popup.format = list(rate = list(format = "f"))
  ) +
  tm_borders(col = "gray40", lwd = 1, lty = "solid", alpha = NA)

Scoping the problem in New York State

counties <- ("/Users/cecilialow-weiner/Downloads/cugir-007865/cty036.shp")
ny_counties <- read_shape(file=counties, as.sf = TRUE)


maternal_mortality_ny <- read_csv("/Users/cecilialow-weiner/Desktop/Data Incubator Project /Maternal_deaths_2013.csv")

## Parsed with column specification:
## cols(
##   NAME = col_character(),
##   Live_Births = col_integer(),
##   Maternal_Mortality = col_integer(),
##   COUNTYFP = col_character()
## )

Calculate maternal mortality rate for New York Counties

maternal_mortality_rate_ny <- maternal_mortality_ny %>%
  group_by(NAME) %>%
  mutate(rate=(Maternal_Mortality/Live_Births)*100000) 

maternal_mortality_rate_ny$COUNTYFP <- as.factor(maternal_mortality_rate_ny$COUNTYFP)

merged_counties <- merge(ny_counties,maternal_mortality_rate_ny,by="NAME")

Mapping Maternal Mortality in New York State

Simple Map

tm_shape(merged_counties) +
  tm_fill(
    col = "rate",
    n = 5,
    style = "jenks"
  )

Interactive Map

ttm()

## tmap mode set to plotting

tm_shape(merged_counties) +
  tm_fill(
    col = "rate",
    palette = "GnBu",
    contrast = c(0.2, 0.8),
    n = 5,
    style = "jenks",
    title = "Maternal Mortality Rate",
    legend.format = list(
      fun = function(x) {
        paste0(formatC(x, digits = 1 , format = "f"), "%")
      }
    ),
    popup.vars = c(
      "Maternal Mortality Rate" = "rate"
    ),
    id = "NAME",
    popup.format = list(rate = list(format = "f"))
  ) +
  tm_borders(col = "gray40", lwd = 1, lty = "solid", alpha = NA)

Scoping the Problem by Years

United States from 1990 to 2015

Bring in international data on maternal mortality from world bank

international_maternal_mortality <- read_csv("/Users/cecilialow-weiner/Desktop/Data Incubator Project /international_maternal_mortality_rates.csv")

## Warning: Missing column names filled in: 'X61' [61], 'X62' [62]

## Parsed with column specification:
## cols(
##   .default = col_character(),
##   `1990` = col_integer(),
##   `1991` = col_integer(),
##   `1992` = col_integer(),
##   `1993` = col_integer(),
##   `1994` = col_integer(),
##   `1995` = col_integer(),
##   `1996` = col_integer(),
##   `1997` = col_integer(),
##   `1998` = col_integer(),
##   `1999` = col_integer(),
##   `2000` = col_integer(),
##   `2001` = col_integer(),
##   `2002` = col_integer(),
##   `2003` = col_integer(),
##   `2004` = col_integer(),
##   `2005` = col_integer(),
##   `2006` = col_integer(),
##   `2007` = col_integer(),
##   `2008` = col_integer(),
##   `2009` = col_integer()
##   # ... with 8 more columns
## )

## See spec(...) for full column specifications.

international_cleaned_names <- clean_names(international_maternal_mortality) 

international_cleaned <- c("country_name", "country_code", "x2013")

new_international_data <- international_cleaned_names[international_cleaned]

Create line graph of maternal mortality rate in U.S. from 1990 to 2015

united_states_1990_2015 <- international_cleaned_names %>%
filter(country_name=="United States")
  
us_mm_1990_2015 <- read_csv("/Users/cecilialow-weiner/Desktop/Data Incubator Project /maternal_mortality_US_1990_2015.csv") %>%
  clean_names()

## Parsed with column specification:
## cols(
##   Year = col_integer(),
##   `Maternal Mortality Rate (per 100,000 live births)` = col_integer()
## )

ggplot(data=us_mm_1990_2015, aes(x=year, y=maternal_mortality_rate_per_100_000_live_births))+
  geom_line()+
  geom_point()

New York City from 2006-2015

MM_Rate_NYC_time <- read_csv("/Users/cecilialow-weiner/Desktop/Data Incubator Project /maternal_mortality_NYC_2006_2015.csv")%>%
  clean_names()

## Parsed with column specification:
## cols(
##   Year = col_integer(),
##   `Maternal Mortality Rate (per 100,000 live births)` = col_double()
## )

Create line graph of maternal mortality rate in New York City from 2006 to 2015

ggplot(data=MM_Rate_NYC_time, aes(x=year, y=maternal_mortality_rate_per_100_000_live_births, group=1)) +
  geom_line()+
  geom_point()+
scale_x_continuous(name="Year", limits=c(2006, 2015),breaks=seq(2006,2015,1)) +
  scale_y_continuous(name="Maternal Mortality Rate", limits=c(10, 40),breaks=seq(10,40,2))